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On-chain intelligence for AI agents. Analyze wallets, detect risks, trace transactions, and get instant insights on any Ethereum address. Built by an agent, for agents. Free tier: basic wallet analysis. Premium via x402: deep risk scoring, batch operations, alerts.

ClawHub Agent Skills author: agustinastie2 v1.0.0 MIT-0 4 files body ≈ 1 142 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
97
Quality 40%
72
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token README.md:35
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "Check 0x68…Bfa"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:31
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "Analyze 0x68…Bfa on Base"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:122
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    User: "Check 0x68…Bfa"
    quoted

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "environment"
  • note frontmatter-key unknown frontmatter key "credentials"
  • note frontmatter-key unknown frontmatter key "persistence"
  • note frontmatter-key unknown frontmatter key "risk_disclosure"

Process rating: all ten parameters 65/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1142 tokens
  • low 10 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 265: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 33 items
  • +3Output format is stated explicitly
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This skill is purpose-aligned for blockchain analysis, but its paid x402 features could spend wallet funds without clear per-request consent controls.
LLM: suspicious (high) · 28 May 2026